Abstract. Much effort has gone into the analysis of cardiac function using mathematical and computational models. To fully realise the potential of these studies requires the translation of these models into clinical applications to aid in diagnosis and clinical planning.

To achieve this goal requires the integration of multiple disparate clinical data sets into a common modelling framework. To this end we have developed a coupled electro-mechanics model of the human heart. This model combines patient specific anatomical geometry, active contraction, electrophysiology, tissue heterogeneities and boundary conditions fitted to comprehensive imaging and catheter clinical measurements.

This multi-scale computational model allows us to link sub cellular mechanisms to whole organ function. This provides a novel tool to determine the mechanisms that underpin treatment out comes and offers the ability to determine hidden variables that provide new metrics of cardiac function. Specifically we report on the application of these methods in patients receiving cardiac resynchronisation therapy and ablation for atrial fibrillation.

A list of errata, corrections, and clarifications for Introduction to Uncertainty Quantification can now be found here. In case you spot any mistakes that are not on this list, then please get in touch and I will be happy to post the correction on the errata page.

As part of this conference, Mark Girolami and I will organise a mini-symposium on “Over-confidence in numerical predictions: challenges and solutions” (MS138 and MS153), which will feature a wide range of perspectives, including Bayesian and frequentist (in)consistency, probabilistic numerics, and application fields.